RPC Muon Tomography System

• RPC muon tomography systems utilize resistive gaseous detectors to reconstruct muon trajectories, providing high spatial and temporal resolution for imaging and material identification.
• They are engineered with parallel resistive plates, optimized gas gaps, and advanced electronics to achieve efficiencies above 95% and precise timing below 150 ps.
• Portable configurations enable versatile field applications, from collider experiments to security screening, archaeology, and nuclear waste monitoring.

A Resistive Plate Chamber (RPC) Muon Tomography System is an arrangement of planar gaseous detectors built from resistive electrodes (either high pressure laminate or glass), designed to reconstruct the trajectories of penetrating muons—most often cosmic rays—for imaging and material identification. Utilized in both high-energy physics (HEP) and multidisciplinary applications (such as archaeology, volcanology, nuclear waste monitoring, and security screening), RPC-based tomography systems exploit the precision time and spatial resolution of RPCs, scalability, and robust redundancy. System architectures have evolved from large-area, multi-layer installations in collider experiments to small, portable, gas-tight configurations suitable for remote or confined environments.

1. Detector Principles and Signal Formation

RPCs consist of two parallel resistive plates, separated by a gas gap (typically in the range of 1–2 mm), and operated at voltages sufficient to establish an electric field that enables avalanche multiplication from ionization produced by traversing muons. The passage of a muon induces an initial ionization charge $Q_0$, which is exponentially amplified over the gap:

$Q = Q_0 \cdot \exp(\alpha \cdot d)$

where $\alpha$ is the first Townsend coefficient determined by the gas mixture and electric field, and $d$ is the avalanche gap thickness (Gamage et al., 2021).

For advanced designs, such as hybrid RPCs with high secondary electron emission coatings (e.g., Al$_2$O$_3$, TiO$_2$), the electron multiplication process can be partially shifted from the gas to the solid-state surface, thereby reducing required operation voltages and enhancing efficiency under high flux (Tosun et al., 2022).

Signal readout is typically performed via metallic strips or pixels arranged orthogonally for 2D reconstruction, with electronics that discriminate and digitize the induced signal—either through fast ASIC-based processing (e.g., FEERIC, NINO, PETIROC, MAROC), or through time-over-threshold (TOT) methodologies that enable tracking and energy estimation (Kumari, 2020, Das et al., 2022).

2. System Architectures and Layer Arrangements

Collider-scale Installations

In large-scale HEP experiments (e.g., CMS at the LHC), RPCs are deployed in multiple layers within a muon spectrometer, with both barrel (|η| < 1.2) and endcap (up to |η| ≈ 2.4) coverage. Upgrades have introduced extended layer configurations, such as the transition from a 3- to 4-layer endcap arrangement and the addition of improved RPCs (iRPCs) with thinner gaps and enhanced electronics (Tytgat et al., 2012, Pedraza-Morales, 2018, Kumari, 2020, Voevodina et al., 2019). These configurations enable “N-out-of-M” coincidence logic (e.g., “3-out-of-4”), optimizing trigger efficiency and resilience to individual chamber inefficiencies.

Portable Systems for Tomography

Field-deployable muon tomography systems use smaller RPCs (active areas ranging from 16 × 16 cm² to ~2 m²) in gas-tight modules, arranged in telescopes of typically 4 layers (2 before and 2 after the target volume) to reconstruct incoming and outgoing muon tracks. Double-gap structures and orthogonal strip or pixelated readouts enhance spatial resolution and tracking redundancy (Samalan et al., 2023, Gamage et al., 2022). Gas-tight or sealed operation using pre-filled volumes obviates the need for continuous gas supply, facilitating safe use in remote environments (Ikram et al., 10 Apr 2025, Kumar et al., 2023).

3. Detector Performance: Efficiency, Resolution, and Stability

Efficiency and Working Point

RPCs in modern tomography systems routinely achieve single-chamber efficiencies above 95–98% at operating voltages tailored through HV scans and plateau determination (e.g., working point $WP = \text{Knee} + 120~V$, where “Knee” is the voltage at 95% of maximum efficiency) (Shopova et al., 2016). Pressure and temperature corrections are essential for maintaining stable performance:

$$\text{HV}_{\text{eff}} = \text{HV} \cdot (T_0 / T) \cdot (P / P_0)$$

with typical reference values $T_0 = 293$ K, $P_0 = 1010$ mbar (Shopova et al., 2016).

Spatial and Time Resolution

Spatial resolution is dictated by readout strip or pixel pitch and the cluster size (number of adjacent channels firing); typical system-level resolution is O(1 cm) for large-area telescopes and approaches O(1 mm) for advanced, small-area, multiplexed designs (Saraiva et al., 2022, Basnet et al., 2022). Time resolution varies with electronics and gas composition; CMS iRPC electronics achieve $<150$ ps, while portable systems with MAROC/NINO/APV chips deliver several ns, sufficient for trajectory assignment even in high-rate conditions (Kumari, 2020, Samalan et al., 2023).

Cluster Size and Noise

Cluster sizes are controlled through geometry and electronic threshold settings, with well-designed systems maintaining an average cluster size below 2 to optimize spatial information (Shopova et al., 2016). Intrinsic noise rates in CMS-scale detectors are typically below 0.1 Hz/cm², supporting low fake rates and high-fidelity imaging (Pugliese, 2014).

Long-term studies confirm the stability of surface resistivity (e.g., variations within 10% over months) and efficiency, although slight degradation (down to 75% efficiency after four months) suggests the need for periodic recalibration in extended deployments (Ikram et al., 10 Apr 2025).

4. Data Acquisition, Signal Processing, and Noise Filtering

Modern muon tomography systems leverage high-channel-density, low-power ASICs and FPGA-based DAQ for real-time data acquisition and transmission—often including wireless capabilities for remote control (Gamage et al., 2021, Samalan et al., 2023). Calibration involves per-channel thresholding schemes:

$QDC_{\text{thr}_i} = \mu_i + 3\sigma_i$

where $\mu_i$ and $\sigma_i$ are the pedestal mean and RMS, respectively (Samalan et al., 2023).

Noise filtering strategies combine time coincidence windows, strip multiplicity and clustering (accepting e.g., only single-cluster, 1–2-strip events), and temporal alignment to suppress cross-talk and fake signals. For instance, signals are required to fall within $t \in [610\ \text{ns}, 625\ \text{ns}]$ after trigger in some portable systems (Kumar et al., 2023).

2D multiplexing algorithms—wherein pixels are mapped on shared channels with hardware and software-based demultiplexing—enable large pixel arrays with manageable channel counts and maintain high spatial resolution even at elevated noise rates, though discrimination becomes challenging at noise levels above ~3% (Basnet et al., 2022).

5. Applications: Imaging, Material Identification, and Beyond

Muon tomography systems based on RPC arrays reconstruct 3D images by measuring the passage and deviation (scattering) of muons through target volumes. The root-mean-square scattering angle is parameterized, for example, by the Lynch-Dahl formula:

$$\theta_0 = \frac{13.6~\mathrm{MeV}}{\beta c p} z \sqrt{\frac{x}{X_0} [1 + 0.038 \ln\left( \frac{x z^2}{X_0 \beta^2} \right)]}$$

where $x/X_0$ is the thickness in radiation lengths, and $p$ the muon momentum (Saraiva et al., 2022). Algorithms such as Point-of-Closest Approach (PoCA) are utilized to localize the region of maximal scattering, enabling identification of high-Z materials in applications like cargo scanning, geological investigations, and nuclear waste monitoring.

Experimental studies demonstrate that 5 cm of tungsten can be identified in 10 minutes with a 4-layer, 2 m² RPC telescope; small-area setups can detect muon absorption patterns in compact lead blocks, validated by measuring differences and ratios in strip occupancy with and without the absorber (Saraiva et al., 2022, Kumar et al., 2023, Ikram et al., 10 Apr 2025).

Long-term, gas-tight portable RPCs, with robust DAQ and environmental monitoring, have now been field-tested for deployment in narrow tunnels, underground chambers, and harsh industrial settings—delivering autonomous operation with small event losses due to extended operation or gas aging (Gamage et al., 2022, Gamage et al., 2021, Samalan et al., 2023, Kumar et al., 2023, Ikram et al., 10 Apr 2025).

6. Systematic Advances, Ongoing R&D, and Future Prospects

R&D directions include the development of eco-friendly gas mixtures to replace high GWP gases (such as SF₆ and R134a), the exploration of hybrid designs with solid-state electron emission coatings (to further lower operation voltages and environmental impact), and the transition to ever finer granularity (2D pixelization) with advanced multiplexed readout to maximize resolution without unsustainable increases in power and cost (Tosun et al., 2022, Basnet et al., 2022, Samalan et al., 2023).

Scaling up for large-volume imaging, as for volcanoes or urban environments, remains a practical challenge—addressed by modular architectures, cross-validation among differently designed prototypes, and active monitoring of long-term stability. Parallel developments in front-end electronics (e.g., integration of MAROC or PETIROC chips for 64+ channel compact readout) and in lightweight structural materials (3D-printed carbon-fiber or plastic frames) target reductions in detector mass and potential for rapid redeployment (Gamage et al., 2021, Samalan et al., 2023, Ikram et al., 10 Apr 2025).

In conclusion, RPC muon tomography has reached a level of technical maturity that permits both collider-grade large-area deployments for fundamental physics and advanced, robust, portable systems suited to interdisciplinary imaging. The iterative synergy between high-energy physics R&D and applied muography has yielded a versatile technology stack—characterized by high efficiency, fine spatial and temporal resolution, cost efficacy, and a scalable framework for future innovation.